As communication technologies have improved, businesses and individuals have desired greater functionality in their communication networks. As a nonlimiting example, many businesses have created call center infrastructures in which a customer or other user can call to receive information related to the business. As customers call into the call center, the customer may be connected with a customer service representative to provide the desired information. Depending on the time of call, the subject matter of the call, and/or other data, the customer may be connected with different customer service representatives. As such, depending on these and/or other factors, the customer may be provided with varying levels of customer service with respect to the interaction with the customer service representative. Because most businesses desire to provide the highest possible quality of customer service, many businesses have turned to recording the communication between the customer and the customer service representative. While recording this data has proven beneficial in many cases, many businesses receive call volumes that inhibit the business from reviewing all of the call data received.
As such, many businesses have turned to speech recognition technology to capture the recorded communication data and thereby provide a textual document for review of the communication. While textual documentation of a communication has also proven beneficial, similar issues may exist in that the sheer amount of data may be such that review of the data is impractical.
To combat this problem, a number of businesses have also implemented analytics technologies to analyze the speech-recognized communications. One such technology that has emerged includes large vocabulary continuous speech recognition (LVCSR). LVCSR technologies often convert received audio from the communications into an English translation of the communication in a textual document. From the textual document, analytics may be provided to determine various data related to the communication. Additionally, phonetic speech recognition may be utilized for capturing the communication data.
While these and technologies may provide a mechanism for capturing communication data, oftentimes, the shear amount of data for processing may consume extensive hardware resources. As such, a solution to increase speed and/or reduce resource consumption is desired.